AIMC Topic: Coronary Artery Disease

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Direct evaluation of antiplatelet therapy in coronary artery disease by comprehensive image-based profiling of circulating platelets.

Nature communications
Coronary artery disease (CAD) is a leading cause of death globally. Antiplatelet therapy remains crucial in preventing and treating CAD-associated thrombotic complications, but it concurrently amplifies the risk of bleeding. Unfortunately, traditiona...

Reduced blood EPAC1 protein levels as a marker of severe coronary artery disease: the role of hypoxic foam cell-transformed smooth muscle cells.

Journal of translational medicine
BACKGROUND: Vascular smooth muscle cells loaded with cholesterol (foam-VSMCs) play a crucial role in the progression of human atherosclerosis. Exchange Protein Directly Activated by cAMP 1 (EPAC1) is a critical protein in the regulation of vascular t...

Fast and automatic coronary artery segmentation using nnU-Net for non-contrast enhanced magnetic resonance coronary angiography.

The international journal of cardiovascular imaging
Non-contrast enhanced magnetic resonance coronary angiography (MRCA) is a promising coronary heart disease screening modality. However, its clinical application is hindered by inherent limitations, including low spatial resolution and insufficient co...

Opportunistic assessment of abdominal aortic calcification using artificial intelligence (AI) predicts coronary artery disease and cardiovascular events.

American heart journal
BACKGROUND: Abdominal computed tomography (CT) is commonly performed in adults. Abdominal aortic calcification (AAC) can be visualized and quantified using artificial intelligence (AI) on CTs performed for other clinical purposes (opportunistic CT). ...

Optimising coronary imaging decisions with machine learning: an external validation study.

Open heart
BACKGROUND: Exclusion of coronary stenosis in individuals with suggestive symptoms is challenging. Cardiac CT or coronary angiography is often used but is inefficient and costly and involves risks. Sex-stratified algorithms based on electronic health...

Comparison of machine learning models with conventional statistical methods for prediction of percutaneous coronary intervention outcomes: a systematic review and meta-analysis.

BMC cardiovascular disorders
INTRODUCTION: Percutaneous coronary intervention (PCI) has been the main treatment of coronary artery disease (CAD). In this review, we aimed to compare the performance of machine learning (ML) vs. logistic regression (LR) models in predicting differ...

Bi-variational physics-informed operator network for fractional flow reserve curve assessment from coronary angiography.

Medical image analysis
The coronary angiography-derived fractional flow reserve (FFR) curve, referred to as the Angio-FFR curve, is crucial for guiding percutaneous coronary intervention (PCI). The invasive FFR is the diagnostic gold standard for determining functional sig...

Cross-institutional validation of a polar map-free 3D deep learning model for obstructive coronary artery disease prediction using myocardial perfusion imaging: insights into generalizability and bias.

European journal of nuclear medicine and molecular imaging
PURPOSE: Deep learning (DL) models for predicting obstructive coronary artery disease (CAD) using myocardial perfusion imaging (MPI) have shown potential for enhancing diagnostic accuracy. However, their ability to maintain consistent performance acr...